A Truthful FPTAS Mechanism for Emergency Demand Response in Colocation Data Centers

Abstract

Demand response (DR) is not only a crucial solution to the demand side management but also a vital means of electricity market in maintaining power grid reliability, sustainability and stability. DR can enable consumers (e.g. data centers) to reduce their electricity consumption when the supply of electricity is a shortage. The consumers will be rewarded in the case of DR if they reduce or shift some of their energy usage during peak hours. Aiming at solving the efficiency of DR, in this paper, we present MEDR, a mechanism on emergency DR in colocation data center. First, we formalize the MEDR problem and propose a dynamic programming to solve the optimization version of the problem. We then design a deterministic mechanism as a solution to solve the MEDR problem. We show that our proposed mechanism is truthful. Next, we prove that our mechanism is an FPTAS, i.e., it can be approximated within 1 + for any given > 0, while the running time of our mechanism is polynomial in n and 1/ , where n is the number of tenants in the datacenter. Furthermore, we also give an auction system covering the efficient FPTAS algorithm as bidding decision program for DR in colocation datacenter. Finally, we choose a practical smart grid dataset to build a large number of datasets for simulation in performance evaluation. By evaluating metrics of the approximation ratio of our mechanism, the non-negative utility of tenants and social cost of colocation datacenter, the results demonstrate the effectiveness of our work.

Emergency demand response in edge computing

“…(7c) and (7d) demonstrate at most one feasible set is accepted, and they are guaranteed by h t * in line 19. Thus, the algorithm can be proven feasible in IP (7). Last, by demonstrating φ ij in the initialization and line 20, CORE ensures the non-negative quality of each variable for the dual problem (8).…”

“…Zhou et al [21] investigate a decentralized method in a geo-distributed data center. Zhou et al [22] and Chen et al [7] both study the FPTAS auction to design a truthful and energy-saving scheme. However, their assumptions of allocation in response to demand are barely offline situations.…”

“…We use OPT 1 and OPT 2 to denote the optimal objective values of (4) and (7). The equivalence between the two program indicates OPT 1 = OPT 2 .…”

“…However, they cannot be applied to edge EDR directly. Previous work either only focuses on electricity procurement [6,7] or does not consider the electricity consumption in scheduling algorithm design [8,9]. More discussions can be found in Section 2.…”

Emergency Demand Response in Edge Computing

“…However, they cannot be applied to edge EDR directly. Previous work either only focuses on electricity procurement [6,7], or does not consider the electricity consumption in scheduling algorithm design [8,9]. More discussions can be found in Sec.…”